Image Normalization in the range 0 to 1

 Accepted Answer

Use mat2gray() or im2double(). Hopefully you have the image processing Toolbox.
normImage = mat2gray(yourImage);
normImage = im2double(yourImage);
Also look at stretchlim() and imadjust().

10 Comments

Sapam - are you still alive???
Sapam Jaya
Sapam Jaya on 5 Feb 2014
Edited: Sapam Jaya on 5 Feb 2014
i was sick..thanx
So does my answer solve your question?
i guess no,the value is coming 0.the thing is i have to do dwt then get the low frequency (LL)component.in this LL i have to do a log average transform.the result of this has to be normalized from 0 to 1.in this log average i have to use a rectangular region.is it same as rectangular window.i dont understand this window much so maybe my output is wrong
You can do your log, and then pass that in to mat2gray() like I showed you. The image is already rectangular so I don't know why you say you have to use a rectangular window and don't understand it. There's nothing to do since it's already a rectangle, unless you want a different sized rectangle, for which you can use rbbox() or imrect().
the rectangular window is as per the instruction..this clears much of the doubt..thanx
Can you go ahead and Accept the answer to close it out? Thanks in advance.
How can these normalized images between 0 and 1 be saved in a folder ? Because after I normalized them and saved them the images obtained remain with pixel range between 0 and 255.
Thank you in advance!
If you really want them to have fractional values between 0 and 1, that's not a standard image format so you'll just have to save them with
save('myFile.mat', 'yourImageVariable');
to save them in a .mat file.
Thank you for your help.

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More Answers (3)

Old question but as of R2017b, rescale does exactly this.
B = rescale(A); % Normalizes image (0 to 1, by default)
You can even use this to scale to uint8, for example:
B = rescale(A,0,255); % Normalizes image to [0 255]
Documentation here:
If im is your image
im=(im-min(im(:)))/(max(im(:))-min(im(:)))

1 Comment

I suggest to do this in two steps to avoid the calculation of MIN twice ...
IM = IM - min(IM(:)) ;
IM = IM / max(IM(:)) ;

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Sajid Khan
Sajid Khan on 6 Feb 2014
Edited: DGM on 13 Feb 2023
function image_normalized = imnormalize( image_orig, min_norm, max_norm)
val_max = max(image_orig(:));
val_min = min(image_orig(:));
range = val_max - val_min;
image_normalized = (image_orig - val_min) ./ range; % Then scale to [x,y] via:
range2 = max_norm - min_norm;
image_normalized = (image_normalized*range2) + min_norm;
end
In this function, you can set min_norm = 0 and max_norm = 1 to normalize image to a scale of 0 to 1. If you have any other questions to ask, then you are welcome. I always use this function for normalization purpose. It even works if you have to increase the scale length.

2 Comments

Your function basically does the same thing as the built in function mat2gray().
Rather, mat2gray() only allows the specification of the input levels, assuming the output levels are [0 1]. Sajid's function allows specification of the output levels, while using image extrema as the input levels.
So in that sense, it's more like rescale(), same syntax and everything.

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Asked:

on 12 Dec 2013

Commented:

DGM
on 13 Feb 2023

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